Hands-on Azure SQL setup - You will learn how to create an Azure database, configure an IP firewall, connect to the service, and run queries safely in a real cloud-based SQL environment.
Better database design - You will improve how you design tables and relationships, so you can build data structures with proper keys, constraints, and a stronger foundation for performance.
Confident T-SQL querying - You will master SELECT, FROM, WHERE, GROUP BY, HAVING, and ORDER BY, which will help you write cleaner queries that return exactly the data you need.
Smarter joins and filtering - You will learn how to use joins, set-based operations, TOP, and subqueries to combine data from multiple tables and narrow results without unnecessary mistakes.
Control over script logic - You will work with variables, IF conditions, and loops, giving you the ability to build T-SQL scripts that automate repetitive tasks and organize processing logic.
Choosing data types wisely - You will understand when to use numeric, text, date and time, XML, and other types, helping you reduce errors, store data properly, and simplify later analysis.
Building procedures and functions - You will learn the difference between procedures and functions and create both stored procedures and scalar functions to organize business logic inside the database.
Safer work with data - You will practice transactions, the ACID principle, error handling, and triggers, so you can protect data integrity more effectively and reduce the impact of failed operations.
Before working with Azure SQL components, it is useful to place them within the broader Microsoft ecosystem. The section gives a concise orientation to the MS Azure platform, its role, and the environment in which database services are provisioned and managed.
Azure cloud adoption is often driven by a need for flexible infrastructure and database service options. This part outlines the main capabilities and practical advantages of using Azure, providing the context for later work with SQL solutions in the platform.
Relational thinking begins with understanding how data is organized and linked. The section introduces tables, rows, columns and tuples, then explains relationships, integrity, normalization, and the role of primary and foreign keys in connecting tables correctly.
In Azure SQL, a stable environment starts with correct service configuration and controlled access. Participants create a database, configure a server-level IP firewall, connect and run queries, then clean up resources to manage the lifecycle of a cloud database setup.
Administrative tasks can be handled directly in Transact-SQL instead of relying only on graphical tools. This section focuses on managing SQL database servers and individual databases through scripts, giving participants a language-based approach to routine operational control.
SELECT statements form the core of T-SQL query writing and result shaping. The section combines source definition with FROM, row filtering through WHERE, grouping and HAVING, sorting with ORDER BY, TOP selection, and set-based operations used to combine result sets.
Subqueries help solve selection problems that are difficult to express with a single flat statement. The training covers nested and correlated subqueries as well as the EXISTS operator, with focus on constructing them correctly and improving their efficiency.
When query logic needs intermediate state, variables become a basic control mechanism. This part addresses declaring and assigning values for use in loops and conditions, while also touching on scalar and table-oriented elements connected with DECLARE-based work.
Data types in T-SQL define how values are stored, interpreted and processed. The section reviews numeric, text, date and time, XML, and less common types such as hierarchyid and cursor, with emphasis on selecting suitable representations for different kinds of data.
Controlling execution flow in T-SQL makes scripts and procedural logic responsive to conditions and repetition. Participants use IF for branching decisions and examine loop constructs such as LOOP, WHILE and FOR to manage iterative processing in database code.
At the database design stage, structure has to balance consistency with practical access patterns. The section walks through creating a relational database and compares normalization with denormalization, including the advantages and trade-offs of each approach.
Depending on scope and lifetime, not every table serves the same purpose in SQL environments. The training explains temporary and global tables, focusing on their structure, visibility and practical use when data must be stored only for a session or shared more broadly.
Table design determines both structural correctness and application performance. This section covers creating and dropping tables, identity-based row numbering, data type selection, joins such as INNER JOIN and OUTER JOIN, and integrity constraints used to enforce valid relationships.
Day-to-day database work often centers on modifying existing records safely and precisely. Here the focus is on INSERT, UPDATE and DELETE statements, with attention to how data is added, changed and removed in a controlled way within relational structures.
Choosing between procedures and functions affects how database logic is designed and executed. This part clarifies the practical and technical differences between both constructs, helping participants decide which approach fits a given task, result type, and usage context in T-SQL.
Stored procedures organize repeatable database logic into reusable server-side units. The section explains where procedures are applied, how their structure is built, and how to create them so that execution logic can be encapsulated and maintained in a clear form.
Reliable data changes depend on correct transaction handling in SQL. Participants work with the ACID model, then move to implementation patterns and error handling so that operations remain consistent, recoverable, and controlled when a statement or process fails.
Triggers in T-SQL are used to react automatically to changes and schema operations. The section distinguishes DML triggers for INSERT, UPDATE and DELETE from DDL triggers for CREATE, ALTER and DROP, and shows how both support integrity rules directly at the database level.
Computer literacy - You should be comfortable using a computer, launching applications, copying data, and navigating basic system tools that will be used during the training.
Basic data concepts - You should understand what records, columns, and tables are and be able to read simple data sets, so the examples presented in class will be easier to follow.
Logical thinking - You should be able to analyze relationships and conditions, because the training includes data filtering, table relations, and the logic behind queries and scripts.
Basic technical English - You should recognize basic technical English terms such as SELECT, INSERT, and UPDATE, because T-SQL syntax and command names are based on English keywords.
